基于NMD算法的水电高占比电网低频振荡模态辨识

Low Frequency Oscillation Mode Identification Based on NMD Method in a High Hydro-ratio Power Grid

  • 摘要: 水电高占比电网中的调速控制问题会导致低于0.1 Hz的超低频振荡,与低频振荡混合加大了低频振荡参数辨识的难度。因此本文提出一种基于自适应的时频分析方法-非线性模态分解(Nonlinear mode decomposition,NMD)来对低频振荡进行参数识别。该方法能够根据信号结构提取时频脊线,估得谐波参数,辨别出对应分量真谐波,消除虚假模态分量。并利用提取出分量的频谱熵特征来设定一个停止分解准则,使分解出的非线性模态分量(Nonlinear mode,NM)具备实际物理意义。对每个NM分量进行Hilbert变换(Hilbert transform,HT)求取振荡参数。最后通过自合成测试信号仿真算例、四机二区系统仿真算例和电网实测算例验证所提方法可行性和有效性。

     

    Abstract: The speed governor problems in a high hydro-ratio power grid will lead to ultra-low frequency oscillations with the frequency below 0.1 Hz, which is mixed with the low frequency oscillation increasing difficulty to identify low frequency oscillation parameters. Therefore, an adaptive time-frequency analysis method-nonlinear mode decomposition(NMD) to identify the parameters of low frequency oscillations is proposed. The method can extract the time-frequency ridge according to the signal structure, obtained the harmonic parameters; identifying true harmonics of the corresponding components, the false mode components are eliminated. And it uses the spectral entropy characteristics of the extracted components to set a stop decomposition criterion, making the decomposed nonlinear mode(NM) components have practical physical significance. The oscillation parameters of each NM component are identified with Hilbert transform(HT). Finally, the method is analyzed and validated by self-synthesized signal simulation, the four-machine two-zone system simulation and the real data collected from the power grid. The effectiveness and feasibility of the proposed method are verified by the results.

     

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